Robust technique for anomalous change detection in airborne hyperspectral imagery based on automatic and adaptive band selection

Nicola Acito; Salvatore Resta; Marco DianiGiovanni Corsini

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Robust technique for anomalous change detection in airborne hyperspectral imagery based on automatic and adaptive band selection

机译：Robust technique for anomalous change detection in airborne hyperspectral imagery based on automatic and adaptive band selection

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摘要

A novel technique for anomalous change detection (ACD) in hyperspectral images is presented. The technique embeds a strategy robust to residual misregistration errors that typically affect data collected by airborne platforms. Furthermore, the proposed technique mitigates the negative effects due to random noise, by means of a band selection technique aimed at discarding spectral channels whose useful signal content is low compared to the noise contribution. Band selection is performed on a per-pixel basis by exploiting the estimates of the noise variance accounting also for the presence of the signal-dependent noise component. Real data collected by a new generation airborne hyperspectral camera on a complex urban scenario are considered to test the proposed method. Performance evaluation shows the effectiveness of the proposed approach with respect to a previously proposed ACD algorithm based on the same similarity measure.

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来源
《Optical Engineering》 |2013年第3期|036202-1-036202-14|共14页
作者
Nicola Acito; Salvatore Resta; Marco DianiGiovanni Corsini;
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作者单位

Accademia Navale di Livorno, Dipartimento Armi Navali, Viale Italia 72, 57100 Livorno, Italia;

Universita di Pisa, Dipartimento di Ingegneria dell'Informazione, Via Caruso 16, 56122 Pisa, Italia;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
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Robust technique for anomalous change detection in airborne hyperspectral imagery based on automatic and adaptive band selection

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